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PTIME: Personalized assistance for calendaring

Published: 15 July 2011 Publication History

Abstract

In a world of electronic calendars, the prospect of intelligent, personalized time management assistance seems a plausible and desirable application of AI. PTIME (Personalized Time Management) is a learning cognitive assistant agent that helps users handle email meeting requests, reserve venues, and schedule events. PTIME is designed to unobtrusively learn scheduling preferences, adapting to its user over time. The agent allows its user to flexibly express requirements for new meetings, as they would to an assistant. It interfaces with commercial enterprise calendaring platforms, and it operates seamlessly with users who do not have PTIME. This article overviews the system design and describes the models and technical advances required to satisfy the competing needs of preference modeling and elicitation, constraint reasoning, and machine learning. We further report on a multifaceted evaluation of the perceived usefulness of the system.

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cover image ACM Transactions on Intelligent Systems and Technology
ACM Transactions on Intelligent Systems and Technology  Volume 2, Issue 4
July 2011
272 pages
ISSN:2157-6904
EISSN:2157-6912
DOI:10.1145/1989734
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 15 July 2011
Accepted: 01 February 2011
Revised: 01 February 2011
Received: 01 December 2010
Published in TIST Volume 2, Issue 4

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Author Tags

  1. Personal assistant agents
  2. calendaring
  3. machine learning
  4. preference modeling

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  • (2024)Challenges and Strategies in Personalised Planning Support for University Students with AutismAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3664898(365-373)Online publication date: 27-Jun-2024
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